First-in-Human (FIH) clinical trials represent a critical milestone for neurotechnology startups. Gaining clinical evidence is the ultimate way to convince the clinical field and the investor community of the value of an innovative medical device.
Reaching FIH efficiently — with a device that meets clinical, regulatory, and commercialisation needs — requires more than a technical proof-of-concept. It demands strategic planning across engineering, manufacturing, verification, and clinical pathways.
Here we draw on the firsthand experience of engineers, clinicians, and product developers who have transformed early-stage concepts into functional, manufacturable systems ready for human trials and commercial availability. They highlight 7 essential strategies that neurotech developers can adopt to move confidently and efficiently toward FIH clinical trials.
Each section offers actionable guidance to help teams anticipate critical development milestones, avoid costly missteps, and make the most of limited time and resources. Across each strategy, we share real-world insights, common pitfalls, and actionable recommendations to help innovators anticipate risks, preserve flexibility, and accelerate their progress toward successful FIH trials.
For early-stage neurotech teams, thoughtful planning at each step can significantly reduce development risk, improve clinical outcomes, and maximize strategic value as devices advance toward commercialization.
Explore the strategies
The following 7 strategies address the most important areas of focus for teams moving from early-stage concept to FIH-ready device:
STRATEGY 1
Successfully developing an implantable device requires more than technical excellence; it demands a deep understanding of how the system will interact with real-world clinical environments. Even strong technologies can face hurdles if clinical realities aren’t fully integrated into early design decisions. In an FDA analysis of Class I & II device recalls, they were most often caused by device design issues. Aligning user needs, surgical workflows, and patient requirements from the start ensures efficient progress toward First-in-Human trials.
Even thoroughly validated devices may face unforeseen challenges in real-world clinical use, particularly when complex system-level interactions are involved. For instance, the 2023 recall of over 150,000 implantable pulse generators (IPGs) highlighted the importance of continuously assessing full-system compatibility to ensure patient safety in dynamic clinical environments.
For early-stage companies, this serves as a valuable reminder: thorough testing should go beyond individual components to consider the full system under realistic use conditions. Proactively designing tests that account for all interfaces and mechanical stresses can help surface potential failure points before they impact patient care.
This is the critical gap many early developers face. It’s not enough for a device to perform well in theory; it must fit seamlessly into clinical workflows and patient realities. Without that alignment, adoption slows, costs rise, and market fit becomes a moving target.
To move quickly and efficiently toward FIH, teams must:
Engage clinicians, patients, and payers early.
Ground design decisions in real-world use, not theoretical ideal scenarios.
Prioritize simplicity, usability, and compatibility with current care standards.
Teams must ask targeted questions: “Where will this device be used? By whom? Under what conditions?” to get the insights that can save months of rework later.
Engaging a partner with clinical networks and real-world insight can help ensure early design decisions align with patient and clinician needs. Then, devices can have a stronger development process.
Getting this right means:
Fewer redesigns
Faster regulatory readiness
Stronger fundraising narratives
Most importantly, it brings transformative technology closer to the patients who need it.
“There’s a strong temptation to focus on device performance. But if you don’t think through the full clinical scenario, even great tech can fail.”
Gil Rind
Director of R&D
Neo-Bionica
STRATEGY 2
Proving that a device works in a lab setting is an important milestone. Building a system that can be manufactured consistently, at scale, and to clinical standards is an entirely different challenge. Early-stage developers often encounter unexpected obstacles when moving from prototypes to production units for preclinical studies or FIH trials.
Several factors make consistency in build quality critical for clinical success:
Variability between units can introduce noise into trial results, obscuring true biological outcomes.
Manual assembly differences can cause performance inconsistencies that delay approvals.
Lack of process controls increases the risk of late-stage redesigns and clinical trial setbacks.
Without early planning for manufacturability, teams risk being forced into costly redesigns just as they approach key milestones like FIH trials. Inconsistent components, manual assembly differences, and overlooked process controls can all derail momentum when it matters most.
To minimize risks during scale-up:
Begin manufacturability and process development once a proof of concept is validated.
Design for repeatability and ensure processes reliably produce dozens, then hundreds, of consistent units.
Select materials, components, and vendors with future scale-up needs in mind.
What to do now:
Planning for manufacturability early also streamlines verification testing and regulatory review. A well-controlled, repeatable process builds stronger clinical evidence and reduces the risk of late-stage setbacks.
STRATEGY 3
Sourcing specialized components for early clinical builds presents unique challenges — especially when working with small volumes and highly regulated materials. Even well-planned programs can encounter delays that impact timelines, budgets, or funding milestones.
Three common supply chain hurdles include:
Priority access: Suppliers often prioritize high-volume customers, de-prioritizing small orders from emerging companies.
Limited vendor options: Certified materials like precious metals or implant-grade components are sourced from only a few global suppliers.
Extended lead times: Waiting two to six months for critical components is not unusual, even at early stages.
With proactive planning, teams can avoid cascading delays and keep FIH trials and milestones on track. Without proactive planning, teams risk falling behind schedule as they wait for parts that suppliers aren’t incentivized to rush.
To mitigate supply chain risks:
Use proven, pre-certified components and existing modules where possible.
Place material orders early, even if it means ordering at-risk.
Work with a contract development and manufacturing organisation (CDMO) that maintains safety stock and has strong supplier relationships.
What to do now:
Anticipating long lead times and securing key materials early helps keep development on track and can make the difference between hitting a critical funding milestone or missing it.
STRATEGY 4
Computational modelling offers speed and can be a powerful tool for accelerating early neurotech development, allowing teams to explore design parameters quickly and cost effectively. But, to ensure models translate into safe and reliable clinical performance, early-stage developers need to balance simulation with benchtop testing.
Several challenges can arise when modelling is used in isolation:
Overconfidence in models: Simulation results can give the illusion of precision without real-world validation.
Mismatch with real-world outcomes: Manufacturing variability, material tolerances, and biological environments often differ from idealized models.
Delayed discovery of failure modes: Critical safety or performance issues may only become apparent during physical testing when changes are harder and more expensive to make.
Physical prototypes, whether benchtop systems or devices used in animal studies, offer noisy but essential ground truth data. Simulations provide clean, controlled outputs but must be calibrated against real-world performance to be predictive and reliable. Used together they create a feedback loop that strengthens the entire design process.
Teams that use modelling effectively focus on:
Using simulations to narrow design parameters early and guide physical experiments.
Validating computational models with real-world testing as soon as feasible.
Continuously refining simulations based on discrepancies between predicted and observed outcomes.
What to do now:
This integrated approach minimizes costly redesigns and builds confidence that the device will perform safely and reliably in human trials.
STRATEGY 5
Effective verification testing isn’t just about proving that a device meets specifications, but building confidence that it will perform reliably in the real world. For implantable neurotechnology, testing strategies must carefully combine regulatory rigor, user risk mitigation, and the realities of early-stage development budgets.
Efficient, risk-based testing is critical for keeping early milestones — especially FIH trials — on track. However, several challenges make early verification testing complex:
Testing can be destructive and costly, requiring the sacrifice of valuable prototypes.
Poorly planned test sequences can generate unnecessary data that bogs down submissions.
Missed user risk scenarios can lead to incomplete testing and expensive late-stage redesigns.
Not everything can be anticipated or tested for, but focusing on real-world clinical risks early helps shape smarter verification strategies. While not every failure can be predicted, foreseeable risks must be identified early and addressed through targeted testing.
Early collaboration with verification experts can help ensure that test plans are grounded in user needs, clinical workflows, and likely failure scenarios. Your tests help you build stronger, faster pathways to FIH trials and avoid costly surprises when the stakes are highest.
Strong verification strategies focus on the following:
Starting with a system-level risk assessment tied to user needs.
Planning non-destructive tests first, moving to destructive tests only when necessary.
Limiting data generation to what is necessary for regulatory submission and risk mitigation.
Designing test units and test flows specifically for validation, not relying on standard prototypes.
Key questions for smarter verification strategies:
What user risks are we prioritizing in our test planning?
Are we starting with non-destructive testing wherever possible?
Have we designed test units specifically for validation — not just repurposed prototypes?
Are we generating only the data necessary to meet regulatory and risk requirements?
Have we built flexibility into our test strategy to adapt if early results reveal unexpected issues?
STRATEGY 6
Selecting the appropriate regulatory pathway is a critical part of early neurotechnology development. Achieving FIH approval requires careful coordination of design validation, clinical study planning, and regulatory submissions.
Defining the right pathway early helps focus system development, optimise resources, and reduce the risk of downstream delays. Consider technical, strategic, or geographic requirements for your regulatory pathway. Doing this early will help companies reach FIH trials efficiently.
Several common challenges can slow progress:
Misaligned strategy: Pursuing unnecessarily high-risk submissions, such as pre-market approval (PMA), when faster or lower-risk pathways like 510(k) or De Novo could be viable.
Overbuilding early designs: Designing systems to meet full market requirements before securing early clinical data.
Overlooking geographic opportunities: Missing faster routes through more flexible regulatory environments, such as early human-use pathways in Australia.
Early engagement with experienced regulatory advisors can help avoid these pitfalls. A well-mapped pathway considers where early human data can be generated most efficiently, what level of design control is needed at each phase, and how clinical evidence will support broader market approvals later.
Instead of attempting full commercial validation immediately, some companies stage their clinical plans by conducting early short-term implants to demonstrate safety and efficacy before moving to larger trials. In markets like Australia, flexible ethics-driven approvals allow developers to gather critical human data faster, with less initial regulatory burden than in the U.S. or EU. This staged approach can de-risk development while preserving flexibility for global expansion.
Smart regulatory and clinical planning focuses on:
Aligning trial strategies with funding and business goals, not just regulatory endpoints.
Matching the clinical study design to the risk classification and intended indication.
Tailoring early trials to maximize learning without committing prematurely to final product specifications.
What to do now:
Engaging an experienced clinical and regulatory advisory firm early—ideally in parallel with engineering decisions—will help innovators anticipate regulatory complexities from the outset and ensure alignment across trial design, indication strategy, and regulatory submissions. For teams seeking that kind of guidance, Neo-Bionica maintains a network of trusted advisors and collaborators we can refer to when appropriate.
STRATEGY 7
Reaching FIH clinical trials often requires balancing short-term clinical goals with long-term commercial objectives. Early-stage companies frequently make necessary compromises to reach critical milestones like developing transitional systems or prioritizing acute trials. These decisions can be valuable, but only if they’re made in the context of long-term strategy.
Without a clear plan, FIH-focused choice can result in:
Transitional systems that demonstrate efficacy but can’t scale into commercial-ready devices.
Short-term design choices that require extensive rework to meet manufacturability, usability, or chronic-use requirements.
Resource misallocation, where significant time and funding are invested in interim devices that do not contribute to the final product strategy.
To maintain momentum beyond FIH, teams should approach design trade-offs with long-term scalability in mind. This balance requires early attention to factors like component selection, modularity, usability, and long-term regulatory needs — even when the immediate goal is simply proving therapeutic effect.
Strategic planning for short-term versus long-term goals should focus on:
Identifying which elements must be in place for FIH versus what can evolve afterward.
Building flexibility into transitional devices to minimize rework after early trials.
Keeping manufacturing, usability, and reimbursement considerations in view from the outset.
What to do now:
When teams align short-term goals with their long-term vision, they reduce rework and protect resources for a smoother transition through clinical and commercial phases.
Conclusion
Building a Faster, Smarter Path to FIH Trials
Early-stage neurotechnology development is complex, but reaching first-in-human trials efficiently is achievable. Each area — from clinical strategy to manufacturing and regulatory execution — presents an opportunity to strengthen your development process and accelerate your path to FIH.
FIH Readiness Checklist
Confirm designs fit real-world clinical workflows, patient use, and stakeholder needs.
Plan for consistent, scalable production immediately after proof-of-concept.
Identify critical materials early and build supplier relationships to manage lead times.
Validate computational models through real-world prototype testing.
Develop risk-based test plans focused on user safety and regulatory needs.
Choose early trial strategies that align with approval and reimbursement goals.
Balance short-term FIH needs with long-term product scalability.
Why Partnering with a CDMO Matters
Bringing an implantable neurotechnology device to first-in-human trials is not just a technical challenge; it’s a coordination challenge across engineering, manufacturing, clinical, and regulatory domains. Early-stage teams often face resource and expertise gaps that can delay progress or drive up costs.
Partnering with a CDMO experienced in neurotechnology helps innovators:
Translate early-stage concepts into scalable, manufacturable designs
Accelerate regulatory readiness and clinical planning
Mitigate supply chain, verification, and manufacturing risks
Preserve limited budgets by minimizing rework and late-stage redesigns
Neo-Bionica brings integrated expertise across design, engineering, manufacturing, and clinical translation — helping neurotechnology startups move faster and maximize their impact at every critical inflection point.
Connect with us to discuss your device and how we can help accelerate your path to clinical trials.
About the Authors
Uli Gommel
Chief Technology Officer
Neo-Bionica
Uli has over 20 years of experience developing Class II and III medical devices, with global leadership roles at Siemens Healthcare and Advanced Bionics. He specialises in end-to-end product development, from design and regulatory clearance to launch and post-market support.
Uli can be contacted directly at ugommel@neo-bionica.com
Gil Rind
Director of R&D
Neo-Bionica
Gil is a biomedical engineer with deep expertise in active implantable neurotechnology. He has led over $20M in early-stage R&D and played a key role at Synchron, helping develop the first FDA-approved commercial brain-computer interface.
Lauren O’Connor
Project Director
Neo-Bionica
Lauren brings over 15 years of global medtech consulting experience, guiding complex projects from concept to commercial launch. With a background in Mechatronics Engineering and Computer Science, she has launched 6 medical technology products to market.